Machine Learning for Finance

Course content

This course begins with the fundamentals of Python programming, providing students with the skills needed for data analysis, visualization, and manipulation using essential libraries such as Pandas, NumPy, and Matplotlib. It is designed as a comprehensive introduction to the application of machine learning in finance for students with no prior programming or data science experience. Students will then progress to core machine learning concepts, including regression, classification, and model validation, all taught within a financial context. The second half of the course focuses on the unique challenges and advanced techniques specific to financial data, such as market prediction, risk assessment, and sentiment analysis. The course culminates in a final project where students will build and evaluate a complete financial machine learning model, moving from raw data to actionable insights.